Triple
T37978375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ofo language |
E947483
|
entity |
| Predicate | laterSettlementArea |
P199702
|
FINISHED |
| Object | Louisiana |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Louisiana | Statement: [Ofo language, laterSettlementArea, Louisiana]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterSettlementArea Context triple: [Ofo language, laterSettlementArea, Louisiana]
-
A.
laterTerritory
Indicates that one territory is a subsequent or successor territory to another in time.
-
B.
laterUSSettlement
chosen
Indicates that one entity represents a U.S. settlement that was established or developed later in time than the other entity.
-
C.
laterServiceArea
Indicates that one service area occurs or becomes applicable after another service area in time.
-
D.
otherSettlement
Indicates that one settlement is another, different settlement distinct from the primary or reference settlement.
-
E.
possibleSettlementAt
Indicates that a settlement could potentially be established or located at a given place or site.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76ef7db908190bba6086673a32300 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a0160834e388190908591b300954d29 |
completed | May 11, 2026, 4:52 a.m. |
| PD | Predicate disambiguation | batch_6a01602a83408190a11d754bdc7da0e9 |
completed | May 11, 2026, 4:50 a.m. |
Created at: May 3, 2026, 4:20 p.m.